Genetic-based conservation status indicators applied to endemics with restricted distributions: a case for eastern Amazonian cangas plants
Bibliographic record
Abstract
BACKGROUND AND AIMS: Critical analyses of genetic data are essential to assessing the conservation status of populations and species and establishing strategies for their protection, which include best monitoring and management practices. This is especially crucial for endemic species with restricted distribution ranges. METHODS: We used genomic data to evaluate the efficacy of Kunming-Montreal Global Biodiversity Framework (GBF) genetic indicators in assessing the conservation status of three endemic plants to the ironstone outcrops (cangas) from the Amazon: Carajasia cangae, Parapiqueria cavalcantei and Ipomoea cavalcantei. We also simulated population bottlenecks to estimate potential effects of future habitat fragmentation. KEY RESULTS: Carajasia cangae and P. cavalcantei exhibited low effective population sizes (NE), low genetic diversity and high inbreeding. Simulations indicated a decrease in genetic diversity and an increase in inbreeding within decades triggered by NE decline. Conversely, I. cavalcantei retains larger NE, greater genetic diversity and low inbreeding, and it demands attention relative to the maintenance of the two genetically distinct populations. Parameters estimated for C. cangae and P. cavalcantei are likely to reflect their higher self-reproduction rates, as opposed to I. cavalcantei, which is self-incompatible. We highlight some problems regarding the application of GBF genetic indicators to predominantly selfing species, such as the fact that their ratio of effective to census population size is far lower than 10 % (the usual threshold to obtain NE when genetic data are unavailable), and their NE often falls below the threshold of 500 to maintain the species long-term evolutionary potential. CONCLUSIONS: We suggest that the reproductive system of endemic plants should be considered to refine guidelines and improve the application of genetic indicators, such as a more appropriate minimum NE and group-specific ratios of effective to census population size. Applying these constraints to GBF indicators might also be appropriate to other organisms with similar biology, independent of their levels of endemism.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".